Research collaboration is often seen as a driver of growth—sparking new ideas, broadening perspectives, and strengthening institutions through shared expertise. 

HKUST has historically performed well in this area. Between 2019 to 2023 (the assessment period for the QS World University Rankings 2026), 74.7% of HKUST’s publications involved international partners.

In SciVal, “international collaboration” is defined by volume. A publication is classified as ‘international’ if it has more than one author, and the authors’ affiliations span more than one country/region, as identified by country code.

Based on this definition (and noting that Hong Kong is assigned a distinct country/region code), HKUST ranks among one of Hong Kong’s most internationally collaborative institutions, alongside local peers such as PolyU (75.4%).  

However, does high volume mean high global reach? 

Two ways to define “global”: Volume vs. network diversity 

Most metrics, including SciVal’s International Collaboration indicator, measure collaboration by volume.  In other words, this perspective asks: 

• Of all publications, what percentage of our papers have a co-author from another country/region? 

This volume‑based view is widely used and effective for capturing the frequency of cross‑border collaboration.

However, volume alone does not fully capture the nature of a research network. To understand the breadth and resilient our collaborations, the QS International Research Network (IRN) offers a complementary perspective.

Rather than counting the number of publications, the IRN focuses on network diversity and sustained partnerships. This metric is adapted from the Margalef Richness Index—a formula originally designed by ecologists to measure the biodiversity of an ecosystem. 

Just as a healthy ecosystem requires diverse species, a healthy research network requires diverse partners. Unlike standard counts of co-authored papers, the IRN looks at how many different countries/regions and institutions are in our network. It also places value on stability, focusing on sustained, established partnerships (three or more co-authored papers) rather than one-time projects.

The IRN Index is calculated:  

IRN Index = L/ln(P)

Where: 

• L = the distinct count of international locations represented in the considered publications
• P = the distinct count of international partner institutions (higher education institutions) in those locations 

In plain terms: 

• SciVal international collaboration rewards how many papers have any cross-border co-authorship. 

• QS IRN rewards how many different places and partner institutions you work with (and whether those relationships are repeated enough to be considered sustainable). 

   

Observations on the HKUST Network  

Viewed through the “volume” lens, HKUST performs strongly:  

• International collaboration (SciVal): 74.7% of outputs include international co-authorship.  

But viewed through the “network diversity” lens, a different pattern emerges:  

• Overall QS IRN score: 49.5, which is notably lower than local peers like PolyU (82.8) and HKU (82.3).  

What does this tell us? It suggests that while HKUST’s research links are robust, they may be concentrated within a smaller circle of research partners. The QS IRN score rewards a wide network across more regions instead of focusing on a deeper or single-region partnership.  

Data for Comparison: 

The table below summarizes these different metrics. You can hover over the spot of the institutions on the map to see the details by subject. You can also verify the IRN Index by adjusting the value on ‘Valid Partners” or “Partners Location”.

See the Pen Collaboration_map by lee chung (@lee-chung) on CodePen.

A concrete example: Arts & Humanities partner footprint 

The Arts & Humanities subject area illustrates this contrast well. Among top partners: 

• HKUST’s top 20 partners come from 5 regions (China, Macao, United States, Singapore, United Kingdom).
• PolyU’s top 20 partners come from 7 regions (China, United Kingdom, South Africa, Macao, Ghana, Singapore, Australia). 

See the Pen institutional collaboration by lee chung (@lee-chung) on CodePen.

This snapshot highlights the key difference: while HKUST shows a high volume of international collaboration, some peer institutions maintain a broader geographic footprint. 

Reflections and limitations 

It is important to view the IRN score strictly as a reference. It provides a valuable alternative perspective, but it has distinct limitations. 

• Institution size: The IRN is not a per-faculty ratio. Larger universities naturally generate more connections simply due to their scale.
• Country/region size effects: The IRN counts locations, not distance. For instance, partnering with 30 universities across the United States counts as one location. Partnering with one university each in Taiwan, Macau, and Singapore counts as three locations.
• Cross-sector blind spot: The IRN counts partnerships between Higher Education Institutions (HEIs) only. This definition creates a blind spot for cross-sector collaboration (partnerships with industry leaders and government institutes, etc).
• Depth vs. breadth: The IRN is not designed to measure the value of deep, long-term bilateral partnerships where HKUST already excels. These relationships remain valuable to scientific advancement, even though they do not increase the “diversity" index.

Looking Forward  

We should not rush to add partners in various locations merely to "fix" a statistic. Instead, we hope this metric serves as a reference to expand our network where it benefits the science—finding researchers in new regions who bring fresh perspectives. 

True global reach is about how far ideas travel, not just how many flags are on a list. We hope this insight supports you as you continue to connect with the world in ways that matter most to your research. 

If you are interested in discussing these metrics, please contact us at lbrs@ust.hk.

Reference:

• Elsevier. (n.d.). International collaboration. SciVal Support Hub. https://service.elsevier.com/app/answers/detail/a_id/28177/supporthub/scival/kw/international+collaboration/
• Elsevier. (n.d.). QS university rankings data. https://www.elsevier.com/academic-and-government/qs-university-rankings-data
• QS Quacquarelli Symonds. (n.d.). International Research Network indicator. https://support.qs.com/hc/en-gb/articles/360021865579-International-Research-Network-Indicator
• QS Quacquarelli Symonds. (n.d.). Processing of citations and papers. https://support.qs.com/hc/en-gb/articles/4411823040018-Processing-of-citations-and-papers